Modeling seasonal influenza outbreak in a closed college campus: impact of pre-season vaccination, in-season vaccination and holidays/breaks

Measuring Perceived Voice Disorders and Quality of Life among Female University Teaching Faculty

BACKGROUND

Occupations that require heavy vocal use can place the person at risk of voice disorders (VDs). Heavy demands on the voice, especially for a long time or with loud back-ground noise, can lead to vocal abuse or misuse. The study aimed to measure the prevalence of perceived voice disorders among the teaching faculty at a female university, identify the risk fac-tors that affect their voice, and determine the effect of perceived voice disorders on their quality of life (QoL).

METHODS

The study sample consisted of female teaching faculty (N = 401). The ques-tionnaire included general sociodemographic data, general voice data, the vocal tract discomfort (VTD) scale, and the World Health Organization Quality of Life assessment (WHOQOL)-BREF.

RESULTS

The results demonstrated that 44.1% of the participants had perceived voice disorders, and stress, reflux, and asthma had a significant relationship with self-perceived voice disorders. Furthermore, the data showed that self-perceived voice disorders negatively impacted the overall QoL of teaching faculty.

CONCLUSIONS

Perceived voice disorders are affected by various factors, including health conditions, medications, and lifestyle choices. Although teaching characteristics and demo-graphic factors are believed to be the cause, in this study they did not significantly contribute to perceived voice disorders. Faculty members with perceived voice disorders have a poorer quality of life, highlighting the need for education on preventative vocal measures and awareness of voice care.

Flu vaccinations: College campus not making the grade. A study of influenza vaccination at an urban public university

Objective: Even healthy college students are vulnerable to severe complications associated with seasonal influenza (flu). Despite national directives to increase influenza vaccination compliance, college campuses remain woefully below national goals. This study aimed to identify factors correlated with the decision to voluntarily receive an influenza vaccine. Additionally, students' reasons for non-vaccination were also examined. Participants: 1021 undergraduate students across four professional schools. Methods: A representative cross-sectional survey was conducted at a public, urban university. Results: The survey measured self-reported influenza vaccination: an overall influenza vaccination rate of 38% was identified. Student characteristics associated with increased influenza vaccination included students' enrollment in academic health disciplines; being female; human papillomavirus (HPV) vaccination; and no marijuana use in the last month. Barriers to influenza vaccination included contraindications, mistrust issues, and personal reasons. Conclusion: Universities that can identify facilitators and barriers to voluntary influenza vaccination can assist with program initiatives to improve influenza vaccination compliance rates.

Catch the tweet to fight the flu: Using Twitter to promote flu shots on a college campus

Objective: Over the 2018-2019 flu season we conducted a randomized controlled trial examining the efficacy of a Twitter campaign on vaccination rates. Concurrently we investigated potential interactions between digital social network structure and vaccination status. Participants: Undergratuates at a large midwestern public university were randomly assigned to an intervention (n = 353) or control (n = 349) group. Methods: Vaccination data were collected via monthly surveys. Participant Twitter data were collected through the public-facing Twitter API. Intervention impact was assessed with logistic regression. Standard network science tools examined vaccination coverage over online social networks. Results: The campaign had no effect on vaccination outcome. Receiving a flu shot the prior year had a positive impact on participant vaccination. Evidence of an interaction between digital social network structure and vaccination status was detected. Conclusions: Social media campaigns may not be sufficient for increasing vaccination rates. There may be potential for social media campaigns that leverage network structure.

The re-emergence of influenza following the COVID-19 pandemic in Victoria, Australia, 2021 to 2022

BackgroundCOVID-19 pandemic mitigation measures, including travel restrictions, limited global circulation of influenza viruses. In Australia, travel bans for non-residents and quarantine requirements for returned travellers were eased in November 2021, providing pathways for influenza viruses to be re-introduced.AimWe aimed to describe the epidemiological and virological characteristics of the re-emergence of influenza in Victoria, Australia to inform public health interventions.MethodsFrom 1 November 2021 to 30 April 2022, we conducted an epidemiological study analysing case notification data from the Victorian Department of Health to describe case demographics, interviewed the first 200 cases to establish probable routes of virus reintroduction and examined phylogenetic and antigenic data to understand virus diversity and susceptibility to current vaccines.ResultsOverall, 1,598 notifications and 1,064 positive specimens were analysed. The majority of cases (61.4%) occurred in the 15-34 years age group. Interviews revealed a higher incidence of international travel exposure during the first month of case detections, and high levels of transmission in university residential colleges were associated with return to campus. Influenza A(H3N2) was the predominant subtype, with a single lineage predominating despite multiple importations.ConclusionEnhanced testing for respiratory viruses during the COVID-19 pandemic provided a more complete picture of influenza virus transmission compared with previous seasons. Returned international travellers were important drivers of influenza reemergence, as were young adults, a group whose role has previously been under-recognised in the establishment of seasonal influenza epidemics. Targeting interventions, including vaccination, to these groups could reduce future influenza transmission.

College students' influenza vaccination adoption: Self-reported barriers and facilitators

OBJECTIVE

Influenza attack rates among college students are high. However, little is known about the determinants of students' flu vaccine adoption from their own perspectives. To fill this gap, this study aims to investigate barriers and facilitators to college students' flu vaccine adoption.

METHODS

A total of 545 students offered complete answers to an online survey. Thematic analysis was used for analyzing open-ended questions.

RESULTS

Students' flu vaccine adoption was hindered by their fear associated with the flu vaccine, lack of pertinent knowledge, perceived lack of necessity, negative social influence, and time constraints and convenience concerns. Students were motivated to adopt the flu vaccine for their interest in self-care, positive experience with the flu vaccine adoption, good flu vaccine habits, and recommendations from trusted sources.

CONCLUSIONS

Understanding determinants of students' flu vaccine adoption provides the first step in developing tailored health interventions that may increase students' flu vaccine adoption rates.

College students' influenza vaccine hesitation: a reasoned action investigation with quantitative and qualitative data

This two-wave longitudinal study (performed pre-COVID), using both quantitative and qualitative data, investigated college students’ influenza vaccine hesitancy and confidence using the theory of planned behavior (TPB). At Time 1, college students (n = 277) completed TPB measures and reported past influenza vaccine behavior. At Time 2 (30 days later), participants indicated whether they received the influenza vaccine since Time 1. At Time 2, participants who indicated that they had not received the influenza vaccine since Time 1 also described their most important reasons for not doing so. The TPB model fit the quantitative data well; direct paths from attitude and norms to intention, and from intention to future behavior, were strong and significant. The TPB model explained 71% of the variance in intention and 28% of the variance in future behavior. Neither perceived behavioral control nor past behavior improved the model’s ability to predict intentions or future behavior. From the qualitative data, participants’ reasons for not getting vaccinated focused on perceived behavioral control (e.g., time cost) and attitudes (e.g., unimportance and low susceptibility). Theoretical implications for message development are discussed.

Variation in the timing of Covid-19 communication across universities in the UK

During the Covid-19 pandemic, universities in the UK used social media to raise awareness and provide guidance and advice about the disease to students and staff. We explain why some universities used social media to communicate with stakeholders sooner than others. To do so, we identified the date of the first Covid-19 related tweet posted by each university in the country and used survival models to estimate the effect of university-specific characteristics on the timing of these messages. In order to confirm our results, we supplemented our analysis with a study of the introduction of coronavirus-related university webpages. We find that universities with large numbers of students are more likely to use social media and the web to speak about the pandemic sooner than institutions with fewer students. Universities with large financial resources are also more likely to tweet sooner, but they do not introduce Covid-19 webpages faster than other universities. We also find evidence of a strong process of emulation, whereby universities are more likely to post a coronavirus-related tweet or webpage if other universities have already done so.

Influenza Vaccination Among U.S. College or University Students: A Systematic Review

OBJECTIVE

Influenza is one of the major causes of morbidity. This study summarized major components that influence college/university students' use of the vaccination using Ecological System Theory; and evaluated racial differences in key predictors of influenza vaccination/intention.

DATA SOURCE

Sixteen engines (e.g., PsycINFO, Academic Search Premier, Science Citation Index) were used to search for cross-sectional studies (2009-2019).

STUDY INCLUSION/EXCLUSION CRITERIA

PI/CO criteria were applied (U.S. students, multidimensional ecological system, influenza vaccination/intention).

DATA EXTRACTION

25 cross-sectional studies were included from the initial 810 citations. Four reviewers performed the cross-checking.

DATA SYNTHESIS AND RESULTS

Higher SES (e.g., education, vaccine affordability, healthcare resource) were positively associated with vaccination/intention. Under micro levels, both internal factors (e.g., positive beliefs, perceptions, attitudes) and external factors (e.g., supports/recommendations from physicians, families or peers, information, engagement in campus activities) enhanced influenza vaccination/intention of students. Meso level factors (private university, dorm-residence, or student housing) also influenced influenza vaccination/intention. Despite limited information on the effects of race on influenza vaccination, the current study synthesized the racial variances in vaccination behaviors of students.

CONCLUSIONS

Enhancing positive beliefs, perceptions, or attitudes toward influenza vaccination with students is critical. Information about the safety and effectiveness of vaccination could be provided for students through official media, medical sources/physicians, campaigns, or internet websites. Family-to-student or peer-to-peer awareness campaigns could facilitate the vaccination of students.

Travel health risk perceptions of Chinese international students in Australia - Implications for COVID-19

BACKGROUND

International students frequently return to their country of origin to visit friends and relatives (VFR), and are at increased risk of travel-associated infections. Little is known of their travel health seeking behaviours. China is the biggest source of international students studying in Australia and the unprecedented epidemic of COVID-19 in China makes this an important area of research.

METHODS

Focus groups of Chinese international students were conducted to explore travel health-related knowledge, attitudes and practices. Eligible participants were studying in Sydney, and had travelled to China and Hong Kong to visit friends and relatives in the preceding 18 months. A variety of topics were explored, using a focus group guide. Thematic analysis was undertaken on the transcripts using nVivo software. The list of codes and themes were not pre-determined but developed through content analysis.

RESULTS

Two focus groups were held with a total of 28 participants. Risk perception about VFR travel was generally low among Chinese international students. Pre-travel healthcare was not sought. Students strongly relied on the Internet, social media, parents and friends in China for travel health advice.

CONCLUSION

This research provides insights into Chinese international students as VFR travellers. It confirms students could be a risk population for importations of infections such as COVID-19 because of low risk perception and lack of seeking travel health advice. This can inform health promotion strategies for students.

Increasing Intent to Vaccinate for Seasonal Influenza

Background: The community college student is not currently armed with the resources or prevention information regarding influenza. Less than twenty percent of the college population receives influenza immunization annually.Purpose: The purpose of the project was to evaluate if an evidenced-based influenza and vaccine education intervention will affect nursing students' intent to vaccinate for influenza by increasing knowledge of the influenza vaccine using Zingg and Siegrist's Knowledge Scale.Methods: Participants were recruited voluntarily from their attendance at orientation for incoming nursing students on a specific date and time. Utilizing a computer survey, all seventy-seven participants completed an online pretest before an educational intervention, and then, the results were compared following the educational intervention with a posttest. Parametric tests such as a paired t-test, Pearson's correlation coefficient, one-way analysis of variance (ANOVA), and percent change were utilized to determine whether an educational intervention was effective in improving influenza knowledge and whether there was a change in vaccination intention.Outcomes and Results: The educational intervention in this project resulted in enhancement of influenza knowledge. The implications of this project demonstrated the value of providing an educational intervention to improve knowledge, intent, and willingness to vaccinate for influenza for nursing students at a community college.

Exploring Influenza Vaccine Uptake and Its Determinants among University Students: A Cross-Sectional Study

While vaccination is the only established option to prevent a susceptible host from influenza, we have yet to clarify the decision-making mechanisms of vaccine uptake among Japanese university and college students. We aimed to explore vaccination coverage and the related demographic, sociocultural, and socioeconomic factors among university students. We performed a cross-sectional survey involving 604 students at Hokkaido University. Participants were asked if they received influenza vaccination in advance of the 2018/19 season, and subsequently, their demographic and sociocultural/socioeconomic characteristics were surveyed. We also explored the mechanisms underlying students’ vaccination decisions. Vaccination coverage was estimated at 27.3% (95% confidence interval: 23.7–30.9). Freshmen (p < 0.0001) were significantly associated with choosing vaccination, and their odds ratio of vaccination was 11.3 (95% confidence interval: 6.2–20.7) times greater than students in other years. Among students other than freshmen, students belonging to medicine- and healthcare-related faculties were vaccinated three times more frequently than other students, and the coverage in students from Hokkaido was twice as large as that for students from other prefectures. Moreover, extracurricular activity was a positive predictor of vaccination. Although the coverage was as small as 27.3% among university students, freshmen in Japan have high vaccination coverage, which we believe is associated with the entrance examination during high influenza activity. In addition to exposing students to proper education regarding their risk self-assessment, consciousness raising via appropriate understanding of influenza and its severity and offering vaccination at university health centers at a reasonable cost may promote vaccine acceptance.

Analyzing influenza outbreaks in Russia using an age-structured dynamic transmission model

In this study, we addressed the ability of a minimalistic SEIR model to satisfactorily describe influenza outbreak dynamics in Russian settings. For that purpose, we calibrated an age-specific influenza dynamics model to Russian acute respiratory infection (ARI) incidence data over 2009-2016 and assessed the variability of proportion of non-immune individuals in the population depending on the regarded city, the non-epidemic indicence baseline, the contact structure considered and the used calibration method. The experiments demonstrated the importance of distinguishing characteristics of different age groups, such as contact intensities and background immunity levels. It was also found that the current model calibration process, which relies mostly on ARI incidence, demonstrates notable variation of output parameter values. Employing additional sources of data, such as strain-specific influenza incidence and external assessments on underreporting levels in different age groups, might enhance the plausibility of parameter values obtained by model calibration, along with reducing the assessment variation.

Modeling the Effectiveness of Respiratory Protective Devices in Reducing Influenza Outbreak

Outbreaks of influenza represent an important health concern worldwide. In many cases, vaccines are only partially successful in reducing the infection rate, and respiratory protective devices (RPDs) are used as a complementary countermeasure. In devising a protection strategy against influenza for a given population, estimates of the level of protection afforded by different RPDs is valuable. In this article, a risk assessment model previously developed in general form was used to estimate the effectiveness of different types of protective equipment in reducing the rate of infection in an influenza outbreak. It was found that a 50% compliance in donning the device resulted in a significant (at least 50% prevalence and 20% cumulative incidence) reduction in risk for fitted and unfitted N95 respirators, high-filtration surgical masks, and both low-filtration and high-filtration pediatric masks. An 80% compliance rate essentially eliminated the influenza outbreak. The results of the present study, as well as the application of the model to related influenza scenarios, are potentially useful to public health officials in decisions involving resource allocation or education strategies.

Seasonal Influenza Vaccination amongst Medical Students: A Social Network Analysis Based on a Cross-Sectional Study

Introduction

The Chief Medical Officer for England recommends that healthcare workers have a seasonal influenza vaccination in an attempt to protect both patients and NHS staff. Despite this, many healthcare workers do not have a seasonal influenza vaccination. Social network analysis is a well-established research approach that looks at individuals in the context of their social connections. We examine the effects of social networks on influenza vaccination decision and disease dynamics.

Methods

We used a social network analysis approach to look at vaccination distribution within the network of the Lancaster Medical School students and combined these data with the students’ beliefs about vaccination behaviours. We then developed a model which simulated influenza outbreaks to study the effects of preferentially vaccinating individuals within this network.

Results

Of the 253 eligible students, 217 (86%) provided relational data, and 65% of responders had received a seasonal influenza vaccination. Students who were vaccinated were more likely to think other medical students were vaccinated. However, there was no clustering of vaccinated individuals within the medical student social network. The influenza simulation model demonstrated that vaccination of well-connected individuals may have a disproportional effect on disease dynamics.

Conclusions

This medical student population exhibited vaccination coverage levels similar to those seen in other healthcare groups but below recommendations. However, in this population, a lack of vaccination clustering might provide natural protection from influenza outbreaks. An individual student’s perception of the vaccination coverage amongst their peers appears to correlate with their own decision to vaccinate, but the directionality of this relationship is not clear. When looking at the spread of disease within a population it is important to include social structures alongside vaccination data. Social networks influence disease epidemiology and vaccination campaigns designed with information from social networks could be a future target for policy makers.

A Novel Dynamic Model for Health Economic Analysis of Influenza Vaccination in the Elderly

Introduction

New vaccines are being developed to improve the efficacy of seasonal influenza immunization in elderly persons aged ≥65 years. These products require clinical and economic evaluation to aid policy decisions.

Methods

To address this need, a two-part model has been developed, which we have applied to examine the potential clinical and economic impact of vaccinating elderly persons with adjuvanted trivalent inactivated influenza vaccine (aTIV) relative to conventional trivalent (TIV) and quadrivalent (QIV) vaccines. We compared outcomes in the US population for (1) aTIV in persons aged ≥65 years and QIV in all other age cohorts; (2) QIV in all cohorts; (3) TIV in all cohorts. Low, average, and high intensity seasons with low, average, and high vaccine match scenarios were compared. Probabilistic sensitivity analysis was conducted within each discrete scenario to explore the impact of variation in model inputs on potential outcomes.

Results

Assuming current vaccination coverage rates in the US population with (a) 25% better efficacy of adjuvanted versus non-adjuvanted vaccine against any strain and (b) 35% better efficacy of non-adjuvanted vaccine against matched B versus mismatched B strains, use of aTIV in persons aged ≥65 years and QIV in persons <65 years could reduce influenza cases by 11,166–1,329,200, hospitalizations by 1365–43,674, and deaths by 421–11,320 versus use of QIV in all cohorts. These outcomes are reflected in a corresponding increase in quality-adjusted life-years (QALYs) of 3003–94,084. If the prevalence of mismatched influenza B was >54.5% of all circulating strains, use of QIV in all cohorts would offset the clinical benefits of aTIV. Elderly aTIV or QIV vaccination was associated with improved outcomes over non-adjuvanted TIV in many of the scenarios, particularly in low match seasons of any intensity. Total cost savings (including direct and indirect healthcare costs plus productivity impacts) with aTIV in the elderly versus QIV in the whole population ranged from $27 million (low intensity, low match) to $934 million (high intensity, high match). Univariate sensitivity analysis of relative vaccine prices in the average intensity, average match scenario indicated that aTIV could be marginally cost saving relative to QIV at the currently published Medicare price for influenza vaccines offering enhanced efficacy in the elderly. Elderly vaccination with aTIV was associated with a higher overall cost compared with TIV in only two scenarios (low intensity with average or high match); the incremental cost/QALY relative to TIV was $9980 in the average match scenario and $28,800 in the high match scenario.

Conclusions

Vaccination of persons aged ≥65 years with aTIV has the potential to provide clinical and economic benefit relative to QIV and TIV. The new model allows the assessment of various alternative strategies for available influenza vaccines.

Funding

Novartis Vaccines.

Electronic supplementary material

The online version of this article (doi:10.1007/s40121-015-0076-8) contains supplementary material, which is available to authorized users.

Disease Interventions Can Interfere with One Another through Disease-Behaviour Interactions

Theoretical models of disease dynamics on networks can aid our understanding of how infectious diseases spread through a population. Models that incorporate decision-making mechanisms can furthermore capture how behaviour-driven aspects of transmission such as vaccination choices and the use of non-pharmaceutical interventions (NPIs) interact with disease dynamics. However, these two interventions are usually modelled separately. Here, we construct a simulation model of influenza transmission through a contact network, where individuals can choose whether to become vaccinated and/or practice NPIs. These decisions are based on previous experience with the disease, the current state of infection amongst one's contacts, and the personal and social impacts of the choices they make. We find that the interventions interfere with one another: because of negative feedback between intervention uptake and infection prevalence, it is difficult to simultaneously increase uptake of all interventions by changing utilities or perceived risks. However, on account of vaccine efficacy being higher than NPI efficacy, measures to expand NPI practice have only a small net impact on influenza incidence due to strongly mitigating feedback from vaccinating behaviour, whereas expanding vaccine uptake causes a significant net reduction in influenza incidence, despite the reduction of NPI practice in response. As a result, measures that support expansion of only vaccination (such as reducing vaccine cost), or measures that simultaneously support vaccination and NPIs (such as emphasizing harms of influenza infection, or satisfaction from preventing infection in others through both interventions) can significantly reduce influenza incidence, whereas measures that only support expansion of NPI practice (such as making hand sanitizers more available) have little net impact on influenza incidence. (However, measures that improve NPI efficacy may fare better.) We conclude that the impact of interference on programs relying on multiple interventions should be more carefully studied, for both influenza and other infectious diseases.

Healthy bodies, toxic medicines: college students and the rhetorics of flu vaccination

This article examines flu vaccination beliefs and practices produced during a survey of undergraduate students in Spring 2012 (IRB#10-732). This research uses the methods of rhetorical analysis - or the study of persuasive features and arguments used in language - to examine statements respondents made regarding flu and flu vaccine. In these responses, students generated unique categories of arguments about the perceived dangers of flu vaccination, including the assertion that vaccines cause disease (including illnesses and conditions other than flu), that vaccines are toxic medicines, and that vaccines carry unknown, population-wide risks that are inadequately acknowledged. This study provides insight into vaccination beliefs and rationales among a population at risk of flu (college students) and suggests that further study of this population may yield important keys to addressing flu vaccine concerns as expressed by college students. Rhetorical analysis also offers a useful set of methods to understanding vaccination beliefs and practices, adding to existing methods of study and analysis of vaccination practices and beliefs in medicine and public health.

Behavioural response in educated young adults towards influenza A(H1N1)pdm09

The purpose of this paper was to determine how contact behaviour change influences the indoor transmission of influenza A(H1N1)pdm09 among school children. We incorporated transmission rate matrices constructed from questionnaire responses into an epidemiological model to simulate contact behaviour change during an influenza epidemic. We constructed a dose-response model describing the relationships between contact rate, viral load, and respiratory symptom scores using published experimental human infection data for A(H1N1)pdm09. Findings showed that that mean numbers of contacts were 5.66 ± 6.23 and 1.96 ± 2.76 d-1 in the 13-19 and 40-59 years age groups, respectively. We found that the basic reproduction number (R 0) was <1 during weekends in pandemic periods, implying that school closures or class suspensions are probably an effective social distancing policy to control pandemic influenza transmission. We conclude that human contact behaviour change is a potentially influential factor on influenza infection rates. For substantiation of this effect, we recommend a future study with more comprehensive control measures.

Global analysis for spread of infectious diseases via transportation networks

We formulate an epidemic model for the spread of an infectious disease along with population dispersal over an arbitrary number of distinct regions. Structuring the population by the time elapsed since the start of travel, we describe the infectious disease dynamics during transportation as well as in the regions. As a result, we obtain a system of delay differential equations. We define the basic reproduction number R(0) as the spectral radius of a next generation matrix. For multi-regional systems with strongly connected transportation networks, we prove that if R(0) ≤ 1 then the disease will be eradicated from each region, while if R(0) > 1 there is a globally asymptotically stable equilibrium, which is endemic in every region. If the transportation network is not strongly connected, then the model analysis shows that numerous endemic patterns can exist by admitting a globally asymptotically stable equilibrium, which may be disease free in some regions while endemic in other regions. We provide a procedure to detect the disease free and the endemic regions according to the network topology and local reproduction numbers. The main ingredients of the mathematical proofs are the inductive applications of the theory of asymptotically autonomous semiflows and cooperative dynamical systems. We visualise stability boundaries of equilibria in a parameter plane to illustrate the influence of the transportation network on the disease dynamics. For a system consisting of two regions, we find that due to spatial heterogeneity characterised by different local reproduction numbers, R(0) may depend non-monotonically on the dispersal rates, thus travel restrictions are not always beneficial.

Analytical modelling of the spread of disease in confined and crowded spaces

Since 1927 and until recently, most models describing the spread of disease have been of compartmental type, based on the assumption that populations are homogeneous and well-mixed. Recent models have utilised agent-based models and complex networks to explicitly study heterogeneous interaction patterns, but this leads to an increasing computational complexity. Compartmental models are appealing because of their simplicity, but their parameters, especially the transmission rate, are complex and depend on a number of factors, which makes it hard to predict how a change of a single environmental, demographic, or epidemiological factor will affect the population. Therefore, in this contribution we propose a middle ground, utilising crowd-behaviour research to improve compartmental models in crowded situations. We show how both the rate of infection as well as the walking speed depend on the local crowd density around an infected individual. The combined effect is that the rate of infection at a population scale has an analytically tractable non-linear dependency on crowd density. We model the spread of a hypothetical disease in a corridor and compare our new model with a typical compartmental model, which highlights the regime in which current models may not produce credible results.

Voice Symptoms and Voice-Related Quality of Life in College Students

Objectives:

The purpose of this study was to examine the prevalence of voice disorders in college students and their effect on the students as shown by quality-of-life indicators.

Methods:

A cross-sectional survey was completed by 545 college students in 2012. The survey included 10 questions from the Voice-Related Quality of Life (V-RQOL), selected voice symptoms, and quality-of-life indicators of functional health and well-being based on the Short Form 36-item Health Survey (SF-36).

Results:

Twenty-nine percent of the college students (mean age, 22.7 years) reported a history of a voice disorder. Hoarseness was the most prevalent voice symptom, but was not correlated with V-RQOL scores. A wobbly or shaky voice, throat dryness, vocal fatigue, and vocal effort explained a significant amount of variance on the social-emotional and physical domains of the V-RQOL index (p < 0.05). Voice symptoms limited emotional and physical functioning as indicated by SF-36 scores.

Conclusions:

Voice disorders significantly influence psychosocial and physical functioning in college students. These findings have important implications for voice-care services in this population.

Mathematical modeling of infectious disease dynamics

Over the last years, an intensive worldwide effort is speeding up the developments in the establishment of a global surveillance network for combating pandemics of emergent and re-emergent infectious diseases. Scientists from different fields extending from medicine and molecular biology to computer science and applied mathematics have teamed up for rapid assessment of potentially urgent situations. Toward this aim mathematical modeling plays an important role in efforts that focus on predicting, assessing, and controlling potential outbreaks. To better understand and model the contagious dynamics the impact of numerous variables ranging from the micro host–pathogen level to host-to-host interactions, as well as prevailing ecological, social, economic, and demographic factors across the globe have to be analyzed and thoroughly studied. Here, we present and discuss the main approaches that are used for the surveillance and modeling of infectious disease dynamics. We present the basic concepts underpinning their implementation and practice and for each category we give an annotated list of representative works.

A model for the emergence of drug resistance in the presence of asymptomatic infections

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We model the emergence of drug resistance in the presence of asymptomatic cases.

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The absence of a preclinical state leads to an overestimation of peak incidence.

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Two reproduction numbers, for drug sensitive or resistant strains, are identified.

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Drug resistant and sensitive strains can coexist in the population.

An analysis of a mathematical model, which describes the dynamics of an aerially transmitted disease, and the effects of the emergence of drug resistance after the introduction of treatment as an intervention strategy is presented. Under explicit consideration of asymptomatic and symptomatic infective individuals for the basic model without intervention the analysis shows that the dynamics of the epidemic is determined by a basic reproduction number R0. A disease-free and an endemic equilibrium exist and are locally asymptotically stable when R0<1 and R0>1 respectively. When treatment is included the system has a basic reproduction number, which is the largest of the two reproduction numbers that characterise the drug-sensitive (R1) or resistant (R2) strains of the infectious agent. The system has a disease-free equilibrium, which is stable when both R1 and R2 are less than unity. Two endemic equilibria also exist and are associated with treatment and the development of drug resistance. An endemic equilibrium where only the drug-resistant strain persists exists and is stable when R2>1 and R1<R2. A second endemic equilibrium exists when R1>1 and R1>R2 and both drug-sensitive and drug-resistant strains are present. The analysis of the system provides insights about the conditions under which the infection will persist and whether sensitive and resistant strains will coexist or not.

Policy resistance undermines superspreader vaccination strategies for influenza

Theoretical models of infection spread on networks predict that targeting vaccination at individuals with a very large number of contacts (superspreaders) can reduce infection incidence by a significant margin. These models generally assume that superspreaders will always agree to be vaccinated. Hence, they cannot capture unintended consequences such as policy resistance, where the behavioral response induced by a new vaccine policy tends to reduce the expected benefits of the policy. Here, we couple a model of influenza transmission on an empirically-based contact network with a psychologically structured model of influenza vaccinating behavior, where individual vaccinating decisions depend on social learning and past experiences of perceived infections, vaccine complications and vaccine failures. We find that policy resistance almost completely undermines the effectiveness of superspreader strategies: the most commonly explored approaches that target a randomly chosen neighbor of an individual, or that preferentially choose neighbors with many contacts, provide at best a 2% relative improvement over their non-targeted counterpart as compared to 12% when behavioral feedbacks are ignored. Increased vaccine coverage in super spreaders is offset by decreased coverage in non-superspreaders, and superspreaders also have a higher rate of perceived vaccine failures on account of being infected more often. Including incentives for vaccination provides modest improvements in outcomes. We conclude that the design of influenza vaccine strategies involving widespread incentive use and/or targeting of superspreaders should account for policy resistance, and mitigate it whenever possible.

Use of seasonal influenza virus titer and respiratory symptom score to estimate effective human contact rates

BACKGROUND

We linked viral titers and respiratory symptom scores for seasonal influenza to estimate the effective contact rate among schoolchildren.

METHODS

We analyzed 274 diary-based questionnaires. In addition, 2 sets of influenza data from published studies were used to investigate the relationship between viral titer, total symptom score, and normalized contact rate in children.

RESULTS

The mean number (SD) of contacts for children in grades 7 to 9 ranged from 9.44 ± 8.68 to 11.18 ± 7.98 person⁻¹ day⁻¹; contact behavior was similar across school grades. The mean number of contacts was 5.66 ± 6.23 person⁻¹ day⁻¹ (range, 0 to 44 person⁻¹ day⁻¹) for the age group of 13 to 19 years. Estimated contact age, household size, contact duration, and contact frequency were the variables most strongly associated with total number of contacts. We also found that a reduction in total respiratory symptom scores among infected individuals had a positive correlation with an increase in the normalized contact rate.

CONCLUSIONS

The relationship between daily virus titer and respiratory symptom score can be used to estimate the effective contact rate in explaining the spread of an airborne transmissible disease. The present findings can be incorporated into population-dynamic models of influenza transmission among schoolchildren.

Protocol for a randomised controlled trial examining the impact of a web-based personally controlled health management system on the uptake of influenza vaccination rates

Background

Online social networking and personally controlled health management systems (PCHMS) offer a new opportunity for developing innovative interventions to prevent diseases of public health concern (e.g., influenza) but there are few comparative studies about patterns of use and impact of these systems.

Methods/Design

A 2010 CONSORT-compliant randomised controlled trial with a two-group parallel design will assess the efficacy of a web-based PCHMS called Healthy.me in facilitating the uptake of influenza vaccine amongst university students and staff. Eligible participants are randomised either to obtain access to Healthy.me or a 6-month waitlist. Participants complete pre-study, post-study and monthly surveys about their health and utilisation of health services. A post-study clinical audit will be conducted to validate self-reports about influenza vaccination and visits to the university health service due to influenza-like illness (ILI) amongst a subset of participants. 600 participants older than 18 years with monthly access to the Internet and email will be recruited. Participants who (i) discontinue the online registration process; (ii) report obtaining an influenza vaccination in 2010 before the commencement of the study; or (iii) report being influenced by other participants to undertake influenza vaccination will be excluded from analysis. The primary outcome measure is the number of participants obtaining influenza vaccination during the study. Secondary outcome measures include: number of participants (i) experiencing ILI symptoms, (ii) absent from or experiencing impairment in work or study due to ILI symptoms, (iii) using health services or medications due to ILI symptoms; (iv) expressing positive or negative attitudes or experiences towards influenza vaccination, via their reasons of receiving (or not receiving) influenza vaccine; and (v) their patterns of usage of Healthy.me (e.g., frequency and timing of hits, duration of access, uptake of specific functions).

Discussion

This study will provide new insights about the utility of online social networking and PCHMS for public health and health promotion. It will help to assess whether a web-based PCHMS, with connectivity to a health service provider, containing information and self-management tools, can improve the uptake of preventive health services amongst university students and staff.

Trial registration

ACTRN12610000386033 (Australian New Zealand Clinical Trials Registry)

An evaluation of behavioral health compliance and microbial risk factors on student populations within a high-density campus

OBJECTIVE

The aim of this Canadian study was to assess student behavioral response to disease transmission risk, while identifying high microbial deposition/transmission sites.

PARTICIPANTS

A student survey was conducted during October 2009.

METHODS

The methods included a survey of students to assess use of health services, vaccination compliance, and hygiene along with a microbial analysis of potential transmission sites targeting specific residence buildings on campus.

RESULTS

Results indicated that most students maintained that they were worried about H1N1 and reported making changes in hygienic behavior, with the majority not planning to be vaccinated. The microbial analysis indicated contamination of fomites in co-ed residences to be higher than either male or female student residences.

CONCLUSIONS

A consideration of physical space along with behavioral factors is required in order to properly assess risk pathways in the establishment of an evidence-based infection control plan for universities and their contiguous communities.

Controlling the spread of disease in schools

Pandemic and seasonal infectious diseases such as influenza may have serious negative health and economic consequences. Certain non-pharmaceutical intervention strategies--including school closures--can be implemented rapidly as a first line of defense against spread. Such interventions attempt to reduce the effective number of contacts between individuals within a community; yet the efficacy of closing schools to reduce disease transmission is unclear, and closures certainly result in significant economic impacts for caregivers who must stay at home to care for their children. Using individual-based computer simulation models to trace contacts among schoolchildren within a stereotypical school setting, we show how alternative school-based disease interventions have great potential to be as effective as traditional school closures without the corresponding loss of workforce and economic impacts.

Can interactions between timing of vaccine-altered influenza pandemic waves and seasonality in influenza complications lead to more severe outcomes?

Vaccination can delay the peak of a pandemic influenza wave by reducing the number of individuals initially susceptible to influenza infection. Emerging evidence indicates that susceptibility to severe secondary bacterial infections following a primary influenza infection may vary seasonally, with peak susceptibility occurring in winter. Taken together, these two observations suggest that vaccinating to prevent a fall pandemic wave might delay it long enough to inadvertently increase influenza infections in winter, when primary influenza infection is more likely to cause severe outcomes. This could potentially cause a net increase in severe outcomes. Most pandemic models implicitly assume that the probability of severe outcomes does not vary seasonally and hence cannot capture this effect. Here we show that the probability of intensive care unit (ICU) admission per influenza infection in the 2009 H1N1 pandemic followed a seasonal pattern. We combine this with an influenza transmission model to investigate conditions under which a vaccination program could inadvertently shift influenza susceptibility to months where the risk of ICU admission due to influenza is higher. We find that vaccination in advance of a fall pandemic wave can actually increase the number of ICU admissions in situations where antigenic drift is sufficiently rapid or where importation of a cross-reactive strain is possible. Moreover, this effect is stronger for vaccination programs that prevent more primary influenza infections. Sensitivity analysis indicates several mechanisms that may cause this effect. We also find that the predicted number of ICU admissions changes dramatically depending on whether the probability of ICU admission varies seasonally, or whether it is held constant. These results suggest that pandemic planning should explore the potential interactions between seasonally varying susceptibility to severe influenza outcomes and the timing of vaccine-altered pandemic influenza waves.